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Muhammad Abdullah Hanif
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2020 – today
- 2024
- [j24]Amira Guesmi
, Muhammad Abdullah Hanif, Bassem Ouni
SAAM: Stealthy Adversarial Attack on Monocular Depth Estimation. IEEE Access 12: 13571-13585 (2024) - [j23]Muhammad Abdullah Hanif
DREAMx: A Data-Driven Error Estimation Methodology for Adders Composed of Cascaded Approximate Units. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 43(11): 3348-3357 (2024) - [c51]Amira Guesmi, Ruitian Ding, Muhammad Abdullah Hanif, Ihsen Alouani, Muhammad Shafique:
DAP: A Dynamic Adversarial Patch for Evading Person Detectors. CVPR 2024: 24595-24604 - [c50]Nandish Chattopadhyay
Defending against Adversarial Patches using Dimensionality Reduction. DAC 2024: 222:1-222:6 - [c49]Sushil Bohara
CuriousRL: Curiosity-Driven Reinforcement Learning for Adaptive Locomotion in Quadruped Robots. IJCNN 2024: 1-8 - [i58]Abdul Basit, Khizar Hussain, Muhammad Abdullah Hanif, Muhammad Shafique:
MedAide: Leveraging Large Language Models for On-Premise Medical Assistance on Edge Devices. CoRR abs/2403.00830 (2024) - [i57]Amira Guesmi
SSAP: A Shape-Sensitive Adversarial Patch for Comprehensive Disruption of Monocular Depth Estimation in Autonomous Navigation Applications. CoRR abs/2403.11515 (2024) - [i56]Nishant Suresh Aswani, Amira Guesmi
Examining Changes in Internal Representations of Continual Learning Models Through Tensor Decomposition. CoRR abs/2405.03244 (2024) - [i55]Muhammad Zaeem Shahzad, Muhammad Abdullah Hanif, Muhammad Shafique:
Robust ADAS: Enhancing Robustness of Machine Learning-based Advanced Driver Assistance Systems for Adverse Weather. CoRR abs/2407.02581 (2024) - [i54]Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique:
PENDRAM: Enabling High-Performance and Energy-Efficient Processing of Deep Neural Networks through a Generalized DRAM Data Mapping Policy. CoRR abs/2408.02412 (2024) - [i53]Aya El Mir, Lukelo Thadei Luoga, Boyuan Chen, Muhammad Abdullah Hanif, Muhammad Shafique:
Democratizing MLLMs in Healthcare: TinyLLaVA-Med for Efficient Healthcare Diagnostics in Resource-Constrained Settings. CoRR abs/2409.12184 (2024) - [i52]Niraj Pudasaini, Muhammad Abdullah Hanif, Muhammad Shafique:
SPAQ-DL-SLAM: Towards Optimizing Deep Learning-based SLAM for Resource-Constrained Embedded Platforms. CoRR abs/2409.14515 (2024) - [i51]Muhammad Zaeem Shahzad, Muhammad Abdullah Hanif, Muhammad Shafique:
DECADE: Towards Designing Efficient-yet-Accurate Distance Estimation Modules for Collision Avoidance in Mobile Advanced Driver Assistance Systems. CoRR abs/2410.19336 (2024) - 2023
- [j22]Amira Guesmi
Physical Adversarial Attacks for Camera-Based Smart Systems: Current Trends, Categorization, Applications, Research Challenges, and Future Outlook. IEEE Access 11: 109617-109668 (2023) - [j21]Muhammad Abdullah Hanif
DAEM: A Data- and Application-Aware Error Analysis Methodology for Approximate Adders. Inf. 14(10): 570 (2023) - [j20]Amira Guesmi
AdvRain: Adversarial Raindrops to Attack Camera-Based Smart Vision Systems. Inf. 14(12): 634 (2023) - [j19]Alberto Marchisio
SeVuc: A study on the Security Vulnerabilities of Capsule Networks against adversarial attacks. Microprocess. Microsystems 96: 104738 (2023) - [j18]Lilas Alrahis
$\tt{PoisonedGNN}$: Backdoor Attack on Graph Neural Networks-Based Hardware Security Systems. IEEE Trans. Computers 72(10): 2822-2834 (2023) - [j17]Ebrahim Farahmand
Design and Analysis of High Performance Heterogeneous Block-based Approximate Adders. ACM Trans. Embed. Comput. Syst. 22(6): 106:1-106:32 (2023) - [c48]Muhammad Abdullah Hanif, Muhammad Shafique
Reduce: A Framework for Reducing the Overheads of Fault-Aware Retraining. DATE 2023: 1-2 - [c47]Jorge Castro-Godínez, Muhammad Abdullah Hanif, Muhammad Shafique
Cross-Layer Approximations for System-Level Optimizations: Challenges and Opportunities. DSN-W 2023: 163-166 - [c46]Ayoub Arous, Amira Guesmi
Exploring Machine Learning Privacy/Utility Trade-Off from a Hyperparameters Lens. IJCNN 2023: 1-10 - [c45]Muhammad Abdullah Hanif, Muhammad Shafique
FAQ: Mitigating the Impact of Faults in the Weight Memory of DNN Accelerators through Fault-Aware Quantization. IJCNN 2023: 1-8 - [i50]Amira Guesmi
AdvRain: Adversarial Raindrops to Attack Camera-based Smart Vision Systems. CoRR abs/2303.01338 (2023) - [i49]Amira Guesmi
APARATE: Adaptive Adversarial Patch for CNN-based Monocular Depth Estimation for Autonomous Navigation. CoRR abs/2303.01351 (2023) - [i48]Ayoub Arous, Amira Guesmi
Exploring Machine Learning Privacy/Utility trade-off from a hyperparameters Lens. CoRR abs/2303.01819 (2023) - [i47]Ebrahim Farahmand, Ali Mahani, Behnam Ghavami, Muhammad Abdullah Hanif, Muhammad Shafique:
scaleTRIM: Scalable TRuncation-Based Integer Approximate Multiplier with Linearization and Compensation. CoRR abs/2303.02495 (2023) - [i46]Lilas Alrahis, Satwik Patnaik, Muhammad Abdullah Hanif, Muhammad Shafique, Ozgur Sinanoglu:
PoisonedGNN: Backdoor Attack on Graph Neural Networks-based Hardware Security Systems. CoRR abs/2303.14009 (2023) - [i45]Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique:
EnforceSNN: Enabling Resilient and Energy-Efficient Spiking Neural Network Inference considering Approximate DRAMs for Embedded Systems. CoRR abs/2304.04039 (2023) - [i44]Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique:
RescueSNN: Enabling Reliable Executions on Spiking Neural Network Accelerators under Permanent Faults. CoRR abs/2304.04041 (2023) - [i43]Muhammad Abdullah Hanif, Muhammad Shafique:
eFAT: Improving the Effectiveness of Fault-Aware Training for Mitigating Permanent Faults in DNN Hardware Accelerators. CoRR abs/2304.12949 (2023) - [i42]Amira Guesmi
DAP: A Dynamic Adversarial Patch for Evading Person Detectors. CoRR abs/2305.11618 (2023) - [i41]Muhammad Abdullah Hanif, Muhammad Shafique:
FAQ: Mitigating the Impact of Faults in the Weight Memory of DNN Accelerators through Fault-Aware Quantization. CoRR abs/2305.12590 (2023) - [i40]Muhammad Abdullah Hanif, Muhammad Shafique:
Reduce: A Framework for Reducing the Overheads of Fault-Aware Retraining. CoRR abs/2305.12595 (2023) - [i39]Vasileios Leon, Muhammad Abdullah Hanif, Giorgos Armeniakos, Xun Jiao, Muhammad Shafique, Kiamal Z. Pekmestzi, Dimitrios Soudris:
Approximate Computing Survey, Part I: Terminology and Software & Hardware Approximation Techniques. CoRR abs/2307.11124 (2023) - [i38]Vasileios Leon, Muhammad Abdullah Hanif, Giorgos Armeniakos, Xun Jiao, Muhammad Shafique, Kiamal Z. Pekmestzi, Dimitrios Soudris:
Approximate Computing Survey, Part II: Application-Specific & Architectural Approximation Techniques and Applications. CoRR abs/2307.11128 (2023) - [i37]Amira Guesmi
SAAM: Stealthy Adversarial Attack on Monoculor Depth Estimation. CoRR abs/2308.03108 (2023) - [i36]Amira Guesmi
Physical Adversarial Attacks For Camera-based Smart Systems: Current Trends, Categorization, Applications, Research Challenges, and Future Outlook. CoRR abs/2308.06173 (2023) - [i35]Kamila Zaman, Alberto Marchisio, Muhammad Abdullah Hanif, Muhammad Shafique:
A Survey on Quantum Machine Learning: Current Trends, Challenges, Opportunities, and the Road Ahead. CoRR abs/2310.10315 (2023) - [i34]Nandish Chattopadhyay, Amira Guesmi
ODDR: Outlier Detection & Dimension Reduction Based Defense Against Adversarial Patches. CoRR abs/2311.12084 (2023) - [i33]Nandish Chattopadhyay, Amira Guesmi
DefensiveDR: Defending against Adversarial Patches using Dimensionality Reduction. CoRR abs/2311.12211 (2023) - 2022
- [j16]Khadija Shaheen
Continual Learning for Real-World Autonomous Systems: Algorithms, Challenges and Frameworks. J. Intell. Robotic Syst. 105(1): 9 (2022) - [j15]Muhammad Abdullah Hanif, Muhammad Shafique
A cross-layer approach towards developing efficient embedded Deep Learning systems. Microprocess. Microsystems 88: 103609 (2022) - [j14]Lilas Alrahis
GNNUnlock+: A Systematic Methodology for Designing Graph Neural Networks-Based Oracle-Less Unlocking Schemes for Provably Secure Logic Locking. IEEE Trans. Emerg. Top. Comput. 10(3): 1575-1592 (2022) - [c44]Rachmad Vidya Wicaksana Putra
SoftSNN: low-cost fault tolerance for spiking neural network accelerators under soft errors. DAC 2022: 151-156 - [c43]Muhammad Abdullah Hanif, Giuseppe Maria Sarda
CoNLoCNN: Exploiting Correlation and Non-Uniform Quantization for Energy-Efficient Low-precision Deep Convolutional Neural Networks. IJCNN 2022: 1-8 - [c42]Shail Dave
Special Session: Towards an Agile Design Methodology for Efficient, Reliable, and Secure ML Systems. VTS 2022: 1-14 - [i32]Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique:
SoftSNN: Low-Cost Fault Tolerance for Spiking Neural Network Accelerators under Soft Errors. CoRR abs/2203.05523 (2022) - [i31]Shail Dave, Alberto Marchisio, Muhammad Abdullah Hanif, Amira Guesmi
Special Session: Towards an Agile Design Methodology for Efficient, Reliable, and Secure ML Systems. CoRR abs/2204.09514 (2022) - [i30]Muhammad Abdullah Hanif, Giuseppe Maria Sarda, Alberto Marchisio
CoNLoCNN: Exploiting Correlation and Non-Uniform Quantization for Energy-Efficient Low-precision Deep Convolutional Neural Networks. CoRR abs/2208.00331 (2022) - 2021
- [j13]Dilshad Sabir
TiQSA: Workload Minimization in Convolutional Neural Networks Using Tile Quantization and Symmetry Approximation. IEEE Access 9: 53647-53668 (2021) - [j12]Nivedita Shrivastava, Muhammad Abdullah Hanif, Sparsh Mittal
A survey of hardware architectures for generative adversarial networks. J. Syst. Archit. 118: 102227 (2021) - [j11]Alberto Marchisio
DESCNet: Developing Efficient Scratchpad Memories for Capsule Network Hardware. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 40(9): 1768-1781 (2021) - [j10]Rachmad Vidya Wicaksana Putra
ROMANet: Fine-Grained Reuse-Driven Off-Chip Memory Access Management and Data Organization for Deep Neural Network Accelerators. IEEE Trans. Very Large Scale Integr. Syst. 29(4): 702-715 (2021) - [j9]Alberto Marchisio
FEECA: Design Space Exploration for Low-Latency and Energy-Efficient Capsule Network Accelerators. IEEE Trans. Very Large Scale Integr. Syst. 29(4): 716-729 (2021) - [c41]Oliver Bringmann, Wolfgang Ecker, Ingo Feldner, Adrian Frischknecht, Christoph Gerum, Timo Hämäläinen, Muhammad Abdullah Hanif, Michael J. Klaiber, Daniel Mueller-Gritschneder
Automated HW/SW co-design for edge AI: state, challenges and steps ahead. CODES+ISSS 2021: 11-20 - [c40]Rachmad Vidya Wicaksana Putra
SparkXD: A Framework for Resilient and Energy-Efficient Spiking Neural Network Inference using Approximate DRAM. DAC 2021: 379-384 - [c39]Muhammad Abdullah Hanif, Muhammad Shafique
DNN-Life: An Energy-Efficient Aging Mitigation Framework for Improving the Lifetime of On-Chip Weight Memories in Deep Neural Network Hardware Architectures. DATE 2021: 729-734 - [c38]Lilas Alrahis, Satwik Patnaik
GNNUnlock: Graph Neural Networks-based Oracle-less Unlocking Scheme for Provably Secure Logic Locking. DATE 2021: 780-785 - [c37]Le Ha Hoang, Muhammad Abdullah Hanif, Muhammad Shafique
TRe-Map: Towards Reducing the Overheads of Fault-Aware Retraining of Deep Neural Networks by Merging Fault Maps. DSD 2021: 434-441 - [c36]Alberto Bosio, Ian O'Connor, Marcello Traiola
Emerging Computing Devices: Challenges and Opportunities for Test and Reliability*. ETS 2021: 1-10 - [c35]Muhammad Shafique
Towards Energy-Efficient and Secure Edge AI: A Cross-Layer Framework ICCAD Special Session Paper. ICCAD 2021: 1-9 - [c34]Lilas Alrahis, Satwik Patnaik
UNTANGLE: Unlocking Routing and Logic Obfuscation Using Graph Neural Networks-based Link Prediction. ICCAD 2021: 1-9 - [c33]Rachmad Vidya Wicaksana Putra
ReSpawn: Energy-Efficient Fault-Tolerance for Spiking Neural Networks considering Unreliable Memories. ICCAD 2021: 1-9 - [i29]Muhammad Abdullah Hanif, Muhammad Shafique:
DNN-Life: An Energy-Efficient Aging Mitigation Framework for Improving the Lifetime of On-Chip Weight Memories in Deep Neural Network Hardware Architectures. CoRR abs/2101.12351 (2021) - [i28]Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique:
SparkXD: A Framework for Resilient and Energy-Efficient Spiking Neural Network Inference using Approximate DRAM. CoRR abs/2103.00421 (2021) - [i27]Faiq Khalid, Muhammad Abdullah Hanif, Muhammad Shafique:
Exploiting Vulnerabilities in Deep Neural Networks: Adversarial and Fault-Injection Attacks. CoRR abs/2105.03251 (2021) - [i26]Khadija Shaheen, Muhammad Abdullah Hanif, Osman Hasan, Muhammad Shafique:
Continual Learning for Real-World Autonomous Systems: Algorithms, Challenges and Frameworks. CoRR abs/2105.12374 (2021) - [i25]Ebrahim Farahmand, Ali Mahani, Muhammad Abdullah Hanif, Muhammad Shafique:
High Performance and Optimal Configuration of Accurate Heterogeneous Block-Based Approximate Adder. CoRR abs/2106.08800 (2021) - [i24]Rachmad Vidya Wicaksana Putra
ReSpawn: Energy-Efficient Fault-Tolerance for Spiking Neural Networks considering Unreliable Memories. CoRR abs/2108.10271 (2021) - [i23]Muhammad Shafique, Alberto Marchisio, Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif:
Towards Energy-Efficient and Secure Edge AI: A Cross-Layer Framework. CoRR abs/2109.09829 (2021) - [i22]Lilas Alrahis, Satwik Patnaik, Muhammad Abdullah Hanif, Muhammad Shafique, Ozgur Sinanoglu:
UNTANGLE: Unlocking Routing and Logic Obfuscation Using Graph Neural Networks-based Link Prediction. CoRR abs/2111.07062 (2021) - 2020
- [j8]Paniti Achararit
APNAS: Accuracy-and-Performance-Aware Neural Architecture Search for Neural Hardware Accelerators. IEEE Access 8: 165319-165334 (2020) - [j7]Muhammad Abdullah Hanif
Resistive Crossbar-Aware Neural Network Design and Optimization. IEEE Access 8: 229066-229085 (2020) - [j6]Hassan Ali
SSCNets: Robustifying DNNs using Secure Selective Convolutional Filters. IEEE Des. Test 37(2): 58-65 (2020) - [j5]Muhammad Kamran Ayub, Muhammad Abdullah Hanif, Osman Hasan, Muhammad Shafique
PEAL: Probabilistic Error Analysis Methodology for Low-power Approximate Adders. ACM J. Emerg. Technol. Comput. Syst. 17(1): 1:1-1:37 (2020) - [j4]Hazoor Ahmad
SuperSlash: A Unified Design Space Exploration and Model Compression Methodology for Design of Deep Learning Accelerators With Reduced Off-Chip Memory Access Volume. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 39(11): 4191-4204 (2020) - [c32]Muhammad Abdullah Hanif, Rehan Hafiz, Osman Hasan
PEMACx: A Probabilistic Error Analysis Methodology for Adders with Cascaded Approximate Units. DAC 2020: 1-6 - [c31]Rachmad Vidya Wicaksana Putra
DRMap: A Generic DRAM Data Mapping Policy for Energy-Efficient Processing of Convolutional Neural Networks. DAC 2020: 1-6 - [c30]Mahum Naseer, Mishal Fatima Minhas, Faiq Khalid, Muhammad Abdullah Hanif, Osman Hasan
FANNet: Formal Analysis of Noise Tolerance, Training Bias and Input Sensitivity in Neural Networks. DATE 2020: 666-669 - [c29]Alberto Marchisio
ReD-CaNe: A Systematic Methodology for Resilience Analysis and Design of Capsule Networks under Approximations. DATE 2020: 1205-1210 - [c28]Le Ha Hoang, Muhammad Abdullah Hanif, Muhammad Shafique
FT-ClipAct: Resilience Analysis of Deep Neural Networks and Improving their Fault Tolerance using Clipped Activation. DATE 2020: 1241-1246 - [c27]Faiq Khalid, Hassan Ali
FaDec: A Fast Decision-based Attack for Adversarial Machine Learning. IJCNN 2020: 1-8 - [c26]Alberto Marchisio
FasTrCaps: An Integrated Framework for Fast yet Accurate Training of Capsule Networks. IJCNN 2020: 1-8 - [c25]Alberto Marchisio
Is Spiking Secure? A Comparative Study on the Security Vulnerabilities of Spiking and Deep Neural Networks. IJCNN 2020: 1-8 - [c24]Muhammad Abdullah Hanif, Muhammad Shafique
Dependable Deep Learning: Towards Cost-Efficient Resilience of Deep Neural Network Accelerators against Soft Errors and Permanent Faults. IOLTS 2020: 1-4 - [c23]Muhammad Abdullah Hanif, Le Ha Hoang, Muhammad Shafique
Cross-layer approaches for improving the dependability of deep learning systems. SCOPES 2020: 78-81 - [i21]Rachmad Vidya Wicaksana Putra
DRMap: A Generic DRAM Data Mapping Policy for Energy-Efficient Processing of Convolutional Neural Networks. CoRR abs/2004.10341 (2020) - [i20]Alberto Marchisio, Vojtech Mrazek, Muhammad Abdullah Hanif, Muhammad Shafique:
DESCNet: Developing Efficient Scratchpad Memories for Capsule Network Hardware. CoRR abs/2010.05754 (2020) - [i19]Lilas Alrahis, Satwik Patnaik, Faiq Khalid, Muhammad Abdullah Hanif, Hani H. Saleh, Muhammad Shafique, Ozgur Sinanoglu:
GNNUnlock: Graph Neural Networks-based Oracle-less Unlocking Scheme for Provably Secure Logic Locking. CoRR abs/2012.05948 (2020)
2010 – 2019
- 2019
- [j3]G. A. Gillani
MACISH: Designing Approximate MAC Accelerators With Internal-Self-Healing. IEEE Access 7: 77142-77160 (2019) - [c22]Muhammad Abdullah Hanif, Faiq Khalid, Muhammad Shafique
CANN: Curable Approximations for High-Performance Deep Neural Network Accelerators. DAC 2019: 6 - [c21]Vojtech Mrazek
autoAx: An Automatic Design Space Exploration and Circuit Building Methodology utilizing Libraries of Approximate Components. DAC 2019: 123 - [c20]Jeff Jun Zhang, Kang Liu, Faiq Khalid, Muhammad Abdullah Hanif, Semeen Rehman, Theocharis Theocharides, Alessandro Artussi, Muhammad Shafique
Building Robust Machine Learning Systems: Current Progress, Research Challenges, and Opportunities. DAC 2019: 175 - [c19]Faiq Khalid, Muhammad Abdullah Hanif, Semeen Rehman, Junaid Qadir
FAdeML: Understanding the Impact of Pre-Processing Noise Filtering on Adversarial Machine Learning. DATE 2019: 902-907 - [c18]Alberto Marchisio
CapsAcc: An Efficient Hardware Accelerator for CapsuleNets with Data Reuse. DATE 2019: 964-967 - [c17]Vojtech Mrazek
ALWANN: Automatic Layer-Wise Approximation of Deep Neural Network Accelerators without Retraining. ICCAD 2019: 1-8 - [c16]Faiq Khalid, Hassan Ali
QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural Network against Adversarial Attacks. IOLTS 2019: 182-187 - [c15]Faiq Khalid, Muhammad Abdullah Hanif, Semeen Rehman, Rehan Ahmed, Muhammad Shafique
TrISec: Training Data-Unaware Imperceptible Security Attacks on Deep Neural Networks. IOLTS 2019: 188-193 - [c14]Muhammad Abdullah Hanif, Muhammad Zuhaib Akbar, Rehan Ahmed, Semeen Rehman, Axel Jantsch
MemGANs: Memory Management for Energy-Efficient Acceleration of Complex Computations in Hardware Architectures for Generative Adversarial Networks. ISLPED 2019: 1-6 - [c13]Alberto Marchisio
Deep Learning for Edge Computing: Current Trends, Cross-Layer Optimizations, and Open Research Challenges. ISVLSI 2019: 553-559 - [p2]Muhammad Abdullah Hanif, Rehan Hafiz, Muhammad Shafique:
Configurable Models and Design Space Exploration for Low-Latency Approximate Adders. Approximate Circuits 2019: 3-23 - [p1]Muhammad Abdullah Hanif, Muhammad Usama Javed, Rehan Hafiz, Semeen Rehman, Muhammad Shafique:
Hardware-Software Approximations for Deep Neural Networks. Approximate Circuits 2019: 269-288 - [i18]Alberto Marchisio, Giorgio Nanfa, Faiq Khalid, Muhammad Abdullah Hanif, Maurizio Martina, Muhammad Shafique:
CapsAttacks: Robust and Imperceptible Adversarial Attacks on Capsule Networks. CoRR abs/1901.09878 (2019) - [i17]Faiq Khalid, Hassan Ali
RED-Attack: Resource Efficient Decision based Attack for Machine Learning. CoRR abs/1901.10258 (2019) - [i16]Alberto Marchisio, Giorgio Nanfa, Faiq Khalid, Muhammad Abdullah Hanif, Maurizio Martina, Muhammad Shafique:
SNN under Attack: are Spiking Deep Belief Networks vulnerable to Adversarial Examples? CoRR abs/1902.01147 (2019) - [i15]Rachmad Vidya Wicaksana Putra
ROMANet: Fine-Grained Reuse-Driven Data Organization and Off-Chip Memory Access Management for Deep Neural Network Accelerators. CoRR abs/1902.10222 (2019) - [i14]Vojtech Mrazek, Muhammad Abdullah Hanif, Zdenek Vasícek, Lukás Sekanina, Muhammad Shafique:
autoAx: An Automatic Design Space Exploration and Circuit Building Methodology utilizing Libraries of Approximate Components. CoRR abs/1902.10807 (2019) - [i13]Alberto Marchisio, Beatrice Bussolino, Alessio Colucci, Muhammad Abdullah Hanif, Maurizio Martina, Guido Masera, Muhammad Shafique:
X-TrainCaps: Accelerated Training of Capsule Nets through Lightweight Software Optimizations. CoRR abs/1905.10142 (2019) - [i12]Vojtech Mrazek, Zdenek Vasícek, Lukás Sekanina, Muhammad Abdullah Hanif, Muhammad Shafique:
ALWANN: Automatic Layer-Wise Approximation of Deep Neural Network Accelerators without Retraining. CoRR abs/1907.07229 (2019) - [i11]Alberto Marchisio, Vojtech Mrazek, Muhammad Abdullah Hanif, Muhammad Shafique:
ReD-CaNe: A Systematic Methodology for Resilience Analysis and Design of Capsule Networks under Approximations. CoRR abs/1912.00700 (2019) - [i10]Le Ha Hoang, Muhammad Abdullah Hanif, Muhammad Shafique:
FT-ClipAct: Resilience Analysis of Deep Neural Networks and Improving their Fault Tolerance using Clipped Activation. CoRR abs/1912.00941 (2019) - [i9]Mahum Naseer, Mishal Fatima Minhas, Faiq Khalid, Muhammad Abdullah Hanif, Osman Hasan, Muhammad Shafique:
FANNet: Formal Analysis of Noise Tolerance, Training Bias and Input Sensitivity in Neural Networks. CoRR abs/1912.01978 (2019) - 2018
- [j2]G. A. Gillani
Squash: Approximate Square-Accumulate With Self-Healing. IEEE Access 6: 49112-49128 (2018) - [j1]Muhammad Abdullah Hanif, Alberto Marchisio
X-DNNs: Systematic Cross-Layer Approximations for Energy-Efficient Deep Neural Networks. J. Low Power Electron. 14(4): 520-534 (2018) - [c12]Salim Ullah
Area-optimized low-latency approximate multipliers for FPGA-based hardware accelerators. DAC 2018: 159:1-159:6 - [c11]Mohammad Taghi Teimoori, Muhammad Abdullah Hanif, Alireza Ejlali, Muhammad Shafique
AdAM: Adaptive approximation management for the non-volatile memory hierarchies. DATE 2018: 785-790 - [c10]Muhammad Shafique
An overview of next-generation architectures for machine learning: Roadmap, opportunities and challenges in the IoT era. DATE 2018: 827-832 - [c9]Muhammad Abdullah Hanif, Rehan Hafiz, Muhammad Shafique
Error resilience analysis for systematically employing approximate computing in convolutional neural networks. DATE 2018: 913-916 - [c8]Bharath Srinivas Prabakaran, Semeen Rehman, Muhammad Abdullah Hanif, Salim Ullah
DeMAS: An efficient design methodology for building approximate adders for FPGA-based systems. DATE 2018: 917-920 - [c7]Alberto Marchisio
HW/SW co-design and co-optimizations for deep learning. INTESA@ESWEEK 2018: 13-18 - [c6]Faiq Khalid, Muhammad Abdullah Hanif, Semeen Rehman, Muhammad Shafique
Security for Machine Learning-Based Systems: Attacks and Challenges During Training and Inference. FIT 2018: 327-332 - [c5]Alberto Marchisio
PruNet: Class-Blind Pruning Method For Deep Neural Networks. IJCNN 2018: 1-8 - [c4]Muhammad Abdullah Hanif, Faiq Khalid, Rachmad Vidya Wicaksana Putra
Robust Machine Learning Systems: Reliability and Security for Deep Neural Networks. IOLTS 2018: 257-260 - [c3]Florian Kriebel, Semeen Rehman, Muhammad Abdullah Hanif, Faiq Khalid, Muhammad Shafique
Robustness for Smart Cyber Physical Systems and Internet-of-Things: From Adaptive Robustness Methods to Reliability and Security for Machine Learning. ISVLSI 2018: 581-586 - [i8]Muhammad Abdullah Hanif, Rachmad Vidya Wicaksana Putra, Muhammad Tanvir, Rehan Hafiz, Semeen Rehman, Muhammad Shafique:
MPNA: A Massively-Parallel Neural Array Accelerator with Dataflow Optimization for Convolutional Neural Networks. CoRR abs/1810.12910 (2018) - [i7]Faiq Khalid, Muhammad Abdullah Hanif, Semeen Rehman, Muhammad Shafique:
ISA4ML: Training Data-Unaware Imperceptible Security Attacks on Machine Learning Modules of Autonomous Vehicles. CoRR abs/1811.01031 (2018) - [i6]Hassan Ali, Hammad Tariq, Muhammad Abdullah Hanif, Faiq Khalid, Semeen Rehman, Rehan Ahmed, Muhammad Shafique:
QuSecNets: Quantization-based Defense Mechanism for Securing Deep Neural Network against Adversarial Attacks. CoRR abs/1811.01437 (2018) - [i5]Hammad Tariq, Hassan Ali, Muhammad Abdullah Hanif, Faiq Khalid, Semeen Rehman, Rehan Ahmed, Muhammad Shafique:
SSCNets: A Selective Sobel Convolution-based Technique to Enhance the Robustness of Deep Neural Networks against Security Attacks. CoRR abs/1811.01443 (2018) - [i4]Faiq Khalid, Muhammad Abdullah Hanif, Semeen Rehman, Junaid Qadir, Muhammad Shafique:
FAdeML: Understanding the Impact of Pre-Processing Noise Filtering on Adversarial Machine Learning. CoRR abs/1811.01444 (2018) - [i3]Faiq Khalid, Muhammad Abdullah Hanif, Semeen Rehman, Muhammad Shafique:
Security for Machine Learning-based Systems: Attacks and Challenges during Training and Inference. CoRR abs/1811.01463 (2018) - [i2]Alberto Marchisio, Muhammad Abdullah Hanif, Semeen Rehman, Maurizio Martina, Muhammad Shafique:
A Methodology for Automatic Selection of Activation Functions to Design Hybrid Deep Neural Networks. CoRR abs/1811.03980 (2018) - [i1]Alberto Marchisio, Muhammad Abdullah Hanif, Muhammad Shafique:
CapsAcc: An Efficient Hardware Accelerator for CapsuleNets with Data Reuse. CoRR abs/1811.08932 (2018) - 2017
- [c2]Muhammad Abdullah Hanif, Rehan Hafiz, Osman Hasan
QuAd: Design and Analysis of Quality-Area Optimal Low-Latency Approximate Adders. DAC 2017: 42:1-42:6 - 2016
- [c1]Muhammad Abdullah Hanif, Asad Anwar Butt, Muhammad Murtaza Khan
Detecting riots using action localization. ICIP 2016: 3031-3035
Coauthor Index
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